The Collegiate Learning Assessment: facts and fantasies

The Collegiate Learning Assessment (CLA) is a computer administered, open-ended (as opposed to multiple-choice) test of analytic reasoning, critical thinking, problem solving, and written communication skills. Because the CLA has been endorsed by several national higher education commissions, it has come under intense scrutiny by faculty members, college administrators, testing experts, legislators, and others. This article describes the CLA's measures and what they do and do not assess, how dependably they measure what they claim to measure, and how CLA scores differ from those on other direct and indirect measures of college student learning. For instance, analyses are conducted at the school rather than the student level and results are adjusted for input to assess whether the progress students are making at their school is better or worse than what would be expected given the progress of "similarly situated" students (in terms of incoming ability) at other colleges.     

THE MALL IS MY FACTORY: REFLECTIONS OF A SERVICE JUNKIE

This paper presents a personal perspective on the history, current research, and emerging topics in the field of Service Operations Management. I see research in the field evolving from a focus on classifications and operations research models in the 1970s and 1980s, to a current focus on laboratory studies, and survey- and case-based research. Selected current research is presented under the following headings: Service encounter design, service quality, drivers of service competitiveness, yield management, and the information revolution and the globalization of services. Examples of creativity in service delivery and some whimsical characteristics of service junkies are also presented.     

The Positive Effects of Easy Goals on Decision Quality and Risk Propensity in an MCPLP Task

In this study the potential performance benefits of easy goals were examined within the multiple cue probability learning paradigm (MCPLP). Specifically, the effects of varying levels of goal difficulty on performance and risk propensity (used to define a form of commitment) were investigated. With few exceptions, previous studies demonstrated support for difficult goals. In this study, contrary to the majority of past evidence, as goals became easier decision quality significantly improved. Moreover, risk propensity increased with easier goals and, as suggested by a post-hoc analysis, had more direct impact on decision makers’ behaviors than goal levels. Goal-related behavior in complex MCPLP tasks appears to significantly differ from the majority of goal evidence in other types of research due to the tendency for subjects to view complex task properties in the same context as goal levels.     

Using Multiple Methods to Provide Prediction Bands of K-12 Enrollment Projections

Population Research and Policy Review - Often, demographers charged with projecting enrollments for school districts are asked to provide a range of future enrollments, as point estimates are not...     

Australia’s national urban policy: The smart cities agenda in perspective

The Australian Government's attempts at national urban policy have been sporadic and inconsistent, under the constraints of constitutional, financial, ideological and political factors. This paper concerns the recent resurgence of national urban policy under the rubric of “smart cities” adopted by the Turnbull Government and carried on by the incumbent Morrison Government. It investigates how this round of smart cities agenda articulates with Australia's political tradition of national urban policy to seek continuity and change, through comparing historical policies, unpacking major smart cities programmes, identifying explanatory factors and critically commenting on its innovation and legacy. Drawing upon these analyses, this paper argues that understanding the smart cities agenda needs to move beyond the political, ideological “to-and-fro” pendulum to national urban policy observed in history. Rather, it resonates with a globalised policy norm established upon the city-based global integration and competition, driven by an imperative of transitioning to a knowledge economy and pursuing innovation capacity. It is too early to judge whether the smart cities agenda will bring changes to Australian cities in the way it wishes, since it involves long-term infrastructure investment and urban development projects. However, a comprehensive and consistent national urban policy to govern the Australian system of cities and towns has not been established yet.     

Industrial Policy Capture in Taiwan and South Korea

Whatever the theoretical merits of an industrial policy, in practice state incentives in support of infant industry are difficult to withdraw once they have been granted. Infant maturation is thereby delayed, resulting in ‘policy capture’ which confers rents on the assisted firms at the expense of consumers and/or taxpayers. The process is well-documented in poorly managed economies pursuing autarkic industrial policies (Auty, 1994a). This article examines evidence of policy capture in well-managed economies pursuing competitive industrial policies. Examples are drawn from the heavy (and chemical) industry drives of South Korea (hereafter Korea) and Taiwan, but the research is first set in the context of the industrial policy debate.     

The effect of omitted covariates in marginal and partially conditional recurrent event analyses

There have been many advances in statistical methodology for the analysis of recurrent event data in recent years. Multiplicative semiparametric rate-based models are widely used in clinical trials, as are more general partially conditional rate-based models involving event-based stratification. The partially conditional model provides protection against extra-Poisson variation as well as event-dependent censoring, but conditioning on outcomes post-randomization can induce confounding and compromise causal inference. The purpose of this article is to examine the consequences of model misspecification in semiparametric marginal and partially conditional rate-based analysis through omission of prognostic variables. We do so using estimating function theory and empirical studies.

     

A comparative study of confidence intervals to assess biosimilarity from analytical data

Assessment of analytical similarity of tier 1 quality attributes is based on a set of hypotheses that tests the mean difference of reference and test products against a margin adjusted for standard deviation of the reference product. Thus, proper assessment of the biosimilarity hypothesis requires statistical tests that account for the uncertainty associated with the estimations of the mean differences and the standard deviation of the reference product. Recently, a linear reformulation of the biosimilarity hypothesis has been proposed, which facilitates development and implementation of statistical tests. These statistical tests account for the uncertainty in the estimation process of all the unknown parameters. In this paper, we survey methods for constructing confidence intervals for testing the linearized reformulation of the biosimilarity hypothesis and also compare the performance of the methods. We discuss test procedures using confidence intervals to make possible comparison among recently developed methods as well as other previously developed methods that have not been applied for demonstrating analytical similarity. A computer simulation study was conducted to compare the performance of the methods based on the ability to maintain the test size and power, as well as computational complexity. We demonstrate the methods using two example applications. At the end, we make recommendations concerning the use of the methods.